Title :
Gaussian Robust Sequential and Predictive Coding
Author :
Lin Song ; Jun Chen ; Jia Wang ; Tie Liu
Author_Institution :
Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
Abstract :
We introduce two new source coding problems: robust sequential coding and robust predictive coding. For the Gauss-Markov source model with the mean squared error distortion measure, we characterize certain supporting hyperplanes of the rate region of these two coding problems. Our investigation also reveals an information-theoretic minimax theorem and the associated extremal inequalities.
Keywords :
Gaussian processes; Markov processes; least mean squares methods; minimax techniques; sequential codes; source coding; Gauss-Markov source model; Gaussian robust sequential coding; extremal inequalities; information-theoretic minimax theorem; mean squared error distortion measure; rate region; robust predictive coding; source coding; Decoding; Encoding; Image reconstruction; Materials; Predictive coding; Robustness; Vectors; Extremal inequality; Gauss–Markov source; minimax theorem; predictive coding; saddle point; sequential coding;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2013.2245720
